docstr: Calculates the elementwise determinant of the log jacobian. Householder flow
  is measure preserving, so :math:`\log(|detJ|) = 0`
docstr_tok: ["Calculates","the","elementwise","determinant","of","the","log","jacobian",".","Householder","flow","is","measure","preserving",",","so",":","math",":","`","\\log","(","|detJ|",")","=","0","`"]
code: def log_abs_det_jacobian(self, x, y):
      r"""
      Calculates the elementwise determinant of the log jacobian. Householder flow
      is measure preserving, so :math:`\log(|detJ|) = 0`
      """
  
      return torch.zeros(
          x.size()[:-1], dtype=x.dtype, layout=x.layout, device=x.device
      )
  
imports: import math
  import warnings
  from functools import partial
  import torch
  import torch.nn
  from torch.distributions import Transform, constraints
  from pyro.nn import DenseNN
  from ..conditional import ConditionalTransformModule
  from ..torch_transform import TransformModule
  from ..util import copy_docs_from
label_desc: Use image node_id 5 for calling the ConditionedHouseholder obj's underlying member method code with example usage: obj.log_abs_det_jacobian(x, y) and returns: torch